TomoGC: binary tomography by constrained GraphCuts
We present an iterative reconstruction algorithm for binary tomography, called TomoGC, that solves the reconstruction problem based on a constrained graphical model by a sequence of graphcuts. TomoGC reconstructs objects even if a low number of measurements are only given, which enables shorter obse...
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| Main Authors: | , , , |
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| Format: | Chapter/Article |
| Language: | English |
| Published: |
03 November 2015
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| In: |
Pattern Recognition
Year: 2015, Pages: 262-273 |
| DOI: | 10.1007/978-3-319-24947-6_21 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1007/978-3-319-24947-6_21 Verlag, Volltext: https://link.springer.com/chapter/10.1007/978-3-319-24947-6_21 
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| Author Notes: | Jörg Hendrik Kappes, Stefania Petra, Christoph Schnörr, Matthias Zisler |
| Summary: | We present an iterative reconstruction algorithm for binary tomography, called TomoGC, that solves the reconstruction problem based on a constrained graphical model by a sequence of graphcuts. TomoGC reconstructs objects even if a low number of measurements are only given, which enables shorter observation periods and lower radiation doses in industrial and medical applications. We additionally suggest some modifications of established methods that improve state-of-the-art methods. A comprehensive numerical evaluation demonstrates that the proposed method can reconstruct objects from a small number of projections more accurate and also faster than competitive methods. |
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| Item Description: | First online: 03 November 2015 Gesehen am 08.06.2018 |
| Physical Description: | Online Resource |
| ISBN: | 9783319249476 |
| DOI: | 10.1007/978-3-319-24947-6_21 |